--- annotations_creators: [] language: - en language_creators: - found license: - mit multilinguality: - monolingual paperswithcode_id: acronym-identification pretty_name: acl-ocl-corpus size_categories: - 10K>> import pandas as pd >>> df = pd.read_parquet('acl-publication-info.74k.parquet') >>> df acl_id abstract full_text corpus_paper_id pdf_hash ... number volume journal editor isbn 0 O02-2002 There is a need to measure word similarity whe... There is a need to measure word similarity whe... 18022704 0b09178ac8d17a92f16140365363d8df88c757d0 ... None None None None None 1 L02-1310 8220988 8d5e31610bc82c2abc86bc20ceba684c97e66024 ... None None None None None 2 R13-1042 Thread disentanglement is the task of separati... Thread disentanglement is the task of separati... 16703040 3eb736b17a5acb583b9a9bd99837427753632cdb ... None None None None None 3 W05-0819 In this paper, we describe a word alignment al... In this paper, we describe a word alignment al... 1215281 b20450f67116e59d1348fc472cfc09f96e348f55 ... None None None None None 4 L02-1309 18078432 011e943b64a78dadc3440674419821ee080f0de3 ... None None None None None ... ... ... ... ... ... ... ... ... ... ... ... 73280 P99-1002 This paper describes recent progress and the a... This paper describes recent progress and the a... 715160 ab17a01f142124744c6ae425f8a23011366ec3ee ... None None None None None 73281 P00-1009 We present an LFG-DOP parser which uses fragme... We present an LFG-DOP parser which uses fragme... 1356246 ad005b3fd0c867667118482227e31d9378229751 ... None None None None None 73282 P99-1056 The processes through which readers evoke ment... The processes through which readers evoke ment... 7277828 924cf7a4836ebfc20ee094c30e61b949be049fb6 ... None None None None None 73283 P99-1051 This paper examines the extent to which verb d... This paper examines the extent to which verb d... 1829043 6b1f6f28ee36de69e8afac39461ee1158cd4d49a ... None None None None None 73284 P00-1013 Spoken dialogue managers have benefited from u... Spoken dialogue managers have benefited from u... 10903652 483c818c09e39d9da47103fbf2da8aaa7acacf01 ... None None None None None [73285 rows x 21 columns] ``` ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Dataset Creation](#dataset-creation) - [Source Data](#source-data) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** https://github.com/shauryr/ACL-anthology-corpus - **Point of Contact:** shauryr@gmail.com ### Dataset Summary Dataframe with extracted metadata (table below with details) and full text of the collection for analysis : **size 489M** ### Languages en, zh and others ## Dataset Structure Dataframe ### Data Instances Each row is a paper from ACL anthology ### Data Fields | **Column name** | **Description** | | :---------------: | :---------------------------: | | `acl_id` | unique ACL id | | `abstract` | abstract extracted by GROBID | | `full_text` | full text extracted by GROBID | | `corpus_paper_id` | Semantic Scholar ID | | `pdf_hash` | sha1 hash of the pdf | | `numcitedby` | number of citations from S2 | | `url` | link of publication | | `publisher` | - | | `address` | Address of conference | | `year` | - | | `month` | - | | `booktitle` | - | | `author` | list of authors | | `title` | title of paper | | `pages` | - | | `doi` | - | | `number` | - | | `volume` | - | | `journal` | - | | `editor` | - | | `isbn` | - | ## Dataset Creation The corpus has all the papers in ACL anthology - as of September'22 ### Source Data - [ACL Anthology](aclanthology.org) - [Semantic Scholar](semanticscholar.org) # Additional Information ### Licensing Information The ACL OCL corpus is released under the [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/). By using this corpus, you are agreeing to its usage terms. ### Citation Information If you use this corpus in your research please use the following BibTeX entry: @Misc{acl-ocl, author = {Shaurya Rohatgi, Yanxia Qin, Benjamin Aw, Niranjana Unnithan, Min-Yen Kan}, title = {The ACL OCL Corpus: advancing Open science in Computational Linguistics}, howpublished = {arXiv}, year = {2022}, url = {https://huggingface.co/datasets/ACL-OCL/ACL-OCL-Corpus} } ### Acknowledgements We thank Semantic Scholar for providing access to the citation-related data in this corpus. ### Contributions Thanks to [@shauryr](https://github.com/shauryr), [Yanxia Qin](https://github.com/qolina) and [Benjamin Aw](https://github.com/Benjamin-Aw-93) for adding this dataset.